Related papers: Streams and Shells Decoded: A Density-Driven Appro…
Deep observations of faint surface brightness stellar tidal streams in external galaxies with LSST are addressed in this White Paper contribution. We propose using the Wide--Fast--Deep survey that contains several nearby galaxies (at…
We present an analysis of the presence of substructures in the stellar stream of the Palomar 5 globular cluster, as derived from Sloan Digital Sky Survey data. Using a matched filter technique, we recover the positions and sizes of…
By means of direct N-body simulations and simplified numerical models, we study the formation and characteristics of the tidal tails around Palomar 5, along its orbit in the Milky Way potential. Unlike previous findings, we are able to…
Stellar dynamical model globular clusters are introduced into reconstituted versions of the dark matter halos of the Via-Lactea II (VL-2) simulation to follow the star cluster tidal mass loss and stellar stream formation. The clusters…
Accurate modelling of redshift-space distortions (RSD) in galaxy clustering is essential for extracting cosmological information from current and forthcoming large-scale structure surveys. While perturbation theory is reliable on large…
This paper focuses on density-based clustering, particularly the Density Peak (DP) algorithm and the one based on density-connectivity DBSCAN; and proposes a new method which takes advantage of the individual strengths of these two methods…
We present a data-driven method for reconstructing the galactic acceleration field from phase-space measurements of stellar streams. Our approach is based on a flexible and differentiable fit to the stream in phase-space, enabling a direct…
Stellar streams, the debris of tidally disrupted satellites, trace their host's gravitational potential and thus probe dark matter halo structure. While six-dimensional phase-space data of Galactic streams enable precise dark matter halo…
Accurately predicting the abundance and structural evolution of dark matter subhaloes is crucial for understanding galaxy formation, modeling galaxy clustering, and constraining the nature of dark matter. Due to the nonlinear nature of…
Clustering of high-dimensional data sets is a growing need in artificial intelligence, machine learning and pattern recognition. In this paper, we propose a new clustering method based on a combinatorial-topological approach applied to…
We investigate the spatial density configuration of stars around four metal-poor globular clusters (NGC 6266, NGC 6626, NGC 6642 and NGC 6723) in the Galactic bulge region using wide-field deep J, H, and K imaging data obtained with the…
Most current clustering based anomaly detection methods use scoring schema and thresholds to classify anomalies. These methods are often tailored to target specific data sets with "known" number of clusters. The paper provides a streaming…
Cold stellar streams---produced by tidal disruptions of clusters---are long-lived, coherent dynamical features in the halo of the Milky Way. Due to their different ages and different positions in phase space, different streams tell us…
The influence of the Cosmic Web on galaxy formation and evolution is of great observational and theoretical interest. We investigate whether the Cosmic Web leaves an imprint in the spatial clustering of galaxies in the Sloan Digital Sky…
Stream graphs are a very useful mode of representation for temporal network data, whose richness offers a wide range of possible approaches. The various methods aimed at generalising the classical approaches applied to static networks are…
Traditional studies of stellar clusters in external galaxies use surface photometry and therefore focus on systems that are still bright and compact enough to be separated from the stellar background. Consequently, the latter stages of…
Node clustering is a powerful tool in the analysis of networks. We introduce a graph neural network framework, named DIGRAC, to obtain node embeddings for directed networks in a self-supervised manner, including a novel probabilistic…
Clustering algorithms are often used to find subpopulations in exploratory data analysis workflows. Not only the clusters themselves, but also their shape can represent meaningful subpopulations. In this paper, we present FLASC, an…
This paper introduces ASTRA (Algorithm for Stochastic Topological RAnking), a new method for classifying galaxies into cosmic web structures -- voids, sheets, filaments, and knots -- specifically designed for large spectroscopic surveys.…
The galaxy distribution in dark matter-dominated halos is expected to approximately trace the details of the underlying dark matter substructure. In this paper we introduce halo `core-tracking' as a way to efficiently follow the small-scale…